<p>This project focused on building a GPS controlled 6-wheel autonomous robot. It is a self-guided autonomous robot, which can be maneuvered with the help of GPS module and compass together interfaced with the microcontroller Arduino Mega. The 6-wheels of the robot are interfaced with monster motor shield and then connected to the Arduino Mega. The speed of the robot is controlled using PWM signals sent from the Arduino board. When the robot starts, it locates its current position using the GPS module. The destination coordinates are already given in the code. Once the current location is fixed, it calculates the distance and heading between the two points. The compass module tells the current heading of the robot. The final heading is calculated by taking the difference between actual heading and current heading. With the help of final heading angle, the robot moves towards its desired location. As the robot moves close to the destination the distance reduces. The minimum distance is predefined as 5 meters in the algorithm since the precision of GPS module is within the range of 5 to 6 meters. Once the distance is less than 5 meters the robot stops, assuming it has reached to the destination location. </p><p> The purpose of building this robot was to guide the robot to multiple locations autonomously with the destination locations predefined in the algorithm. To maneuver the robot to the multiple locations it is very important to calculate the accurate distance and heading. For this project, the main task was to design an algorithm that can calculate the exact distance between any two locations and guide the robot in the proper direction. The motors used for this project have high torque and the updating speed of the GPS module is slow. It was very important to keep the speed of the motor very low and change the speed of the motor only when there was a need to change the direction of the robot. The algorithm designed was able to fulfill these tasks and guided the robot to multiple locations and reach the final destination. </p>

<p> This thesis builds on a recently developed Failure Recovery Synthesis (FRS) technique for robotic manipulators, which is mounted on a movable platform to achieve an originally specified task after an arm joint failure. The FRS locks in place the failed arm joint and determines a new position for the base of the arm and a new grasping location for the end-effector. </p><p> This work aims towards improving the trajectory planning technique of the FRS in order to generate optimal reaching motions in case of an arm joint failure. Aiming towards improving the robotic trajectory planning technique in the FRS, the work adopts previous results from experimental observations on human elbow constrained reaching movements. The assumption that the end-effector of an elbow locked anthropomorphic robotic manipulator is in contact with a specific surface during the entire movement allows us to describe the contact conditions by using higher order kinematic constraints such as velocities, accelerations, and jerks. By adopting contact specifications at initial and final task locations, kinematic synthesis and path planning techniques enable us to generate an entire end-effector trajectory connecting the two locations. </p><p> The proposed method was validated by comparing its outcome to an actual human elbow-constrained reaching motion profile. The results show a smooth trajectory that closely follows the human hand path.</p><p>

<p>Developing a smart home environment for the assistive living requires great efforts. The key element of the smart environment is the ubiquitous voice user interface with several additional capabilities such as the recognition of several gestures, which can be a new feature of voice controlled devices. There are many identification technologies used in current intelligent guard systems. Relative to other techniques, the voice recognition technology is generally regarded as one of the convenient and safe recognition techniques. The assistive device project has incorporated the technology of voice recognition to perform the GSM calling. Arduino UNO is the microprocessor used to create an interface between the voice module and the GSM module SIM900. Platform was developed using inexpensive hardware and software elements available on the market People with disabilities showed high robustness for assistive device. Sample voice commands were stored in the temporary memory for the ATMEGA 328P when field tests with several sets of voice commands was done. The GSM module SIM900 could easily connect to the local cellular network carriers. Hence voice recognized emergency calling can be the future of biomedical field. </p>

<p> Monocular simultaneous localization and mapping (SLAM) is an important technique that enables very inexpensive environment mapping and pose estimation in small systems such as smart phones and unmanned aerial vehicles. However, the information generated by monocular SLAM is in an arbitrary and unobservable scale, leading to drift and making it difficult to use with other sources of odometry for control or navigation. To correct this, the odometry needs to be aligned with metric scale odometry from another device, or else scale must be recovered from known features in the environment. Typically known environmental features are not available, and for systems such as cellphones or unmanned aerial vehicles (UAV), which may experience sustained, small scale, irregular motion, an IMU is often the only practical option. Because accelerometers measure acceleration and gravity, an inertial measurement unit (IMU) must filter out gravity and track orientation with complex algorithms in order to provide a linear acceleration measurement that can be used to recover SLAM scale. In this thesis, an alternative method will be proposed, which detects and removes gravity from the accelerometer measurement by using the unscaled direction of acceleration derived from the SLAM odometry.</p><p>

<p> Robot mapping consists of using a robotic system to create the cartographic representation, or map, of an environment. This environment can have different shapes, sizes, and may be previously known or unknown. With a map, actions such as rescue, security, and construction, can be meticulously planned in terms of space for better efficiency and accuracy. The robotic platform designed in this industrial project is capable of autonomously creating the map of a previously unknown environment. Therefore, no human input is necessary in its operation. It uses wireless technology to communicate with the computing core, eliminating the necessity of cables to exchange data. In order to gather data from the environment, the mapping robot uses multiple sensors, namely three ultrasonic sensors, a gyroscope sensor, and a rotary encoder. A mapping application is created to receive the data and create a map of the environment. </p>

<p> In dense cluttered environments, autonomous physical agents will face many challenges including limited routes, obstructed sensors, and limited communication. Equipping the agents with inter-agent communication alleviates some of the issues, but providing a mechanism for forming groups allows the agents to work together efficiently by avoiding congestion in tight areas and providing redundancy to accomplish a task. This thesis presents a framework for decentralized collaborative group formations and a framework for augmenting that with a more strategic centralized approach. This thesis will investigate a strategy for the formation of hierarchical ad-hoc groups that provide a simple interface for joining and splitting groups. After formation these groups will use peer to peer algorithms to share sensor data and perform distributed task allocation within the group. The groups can either be controlled by a static base-station or use a decentralized framework if communication to the base-station is lost. When communication is restored, the peer to peer algorithms will be used to spread the data to as many agents as possible to avoid data loss. A radio propagation model is also presented to simulate communication in indoor and simulated environments, as well as estimated propagation for use in path planning. This framework will also allow the agent's high level decision making to modify its role depending on group consensus. </p>

<p> Control of miniature mobile robots in unconstrained environments is an ongoing challenge. Miniature robots often exhibit nonlinear dynamics and obstacle avoidance introduces significant complexity in the control problem. In order to allow for coordinated movements, the robots must know their location relative to the other robots; this is challenging for very small robots operating under severe power and size constraints. This drastically reduces on-board digital processing power and suggests the need for a robust, compact distance sensor and a mixed-signal control system using Extended Kalman Filtering and Randomized Receding Horizon Control to support decentralized coordination of autonomous mini-robots. Error analysis of the sensor suggests that system clock timing jitter is the dominant contributor for sensor measurement uncertainty. Techniques for system identification of model parameters and the design of a mixed-signal computer for mobile robot position estimation are presented. </p>

Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2007. / Source: Dissertation Abstracts International, Volume: 69-02, Section: B, page: 1198. Adviser: Francesco Bullo. Includes bibliographical references (leaves 150-158) Available on microfilm from Pro Quest Information and Learning.

Thèse (M.Sc.A.)--Université de Sherbrooke (Canada), 2007. / Titre de l'écran-titre (visionné le 1 février 2007). In ProQuest dissertations and theses. Publié aussi en version papier.

Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2008. / Source: Dissertation Abstracts International, Volume: 69-11, Section: B, page: 7032. Adviser: Mark W. Spong. Includes bibliographical references (leaves 156-162) Available on microfilm from Pro Quest Information and Learning.